BACKGROUND

CASE STUDY ANALYSIS

CONCLUSION REFERENCES

Identifying stratospheric air intrusions and associated hurricane-force wind events over the north Pacific Ocean

CONTACT kelsey.malloy@noaa.gov michael.folmer@noaa.gov

Motivation • Ocean data is sparse

• Ocean Prediction Center (OPC) – “mariner’s weather lifeline”

• Geostationary Operational Environmental Satellite – R Series (now GOES-16)4 comparable to Japanese Meteorological Agency’s Himawari-8

• Reliance on satellite imagery for marine forecasting

• Responsible for:

• Pacific, Atlantic, Pacific Alaska surface analyses/forecasts – 24, 48, 96 hr

• Wind & wave analyses/forecasts – 24, 48, 96 hr • Warning Services & Decision Support

Research Question: How can integrating satellite data imagery and derived products help forecasters improve prognosis of rapid cyclogenesis and hurricane-force wind events?

Phase I – Identifying stratospheric air intrusions Water Vapor – 6.2, 6.9, 7.3 μm channels Airmass RGB Product AIRS, IASI, ATMS/CrIS total column ozone & ozone anomaly ASCAT (A/B) and AMSR-2 wind data

Stratospheric Air Intrusions AKA: tropopause folds, stratosphere-troposphere exchange (STE), dry intrusion • Exchanges of air between stratosphere and troposphere

• Importance to weather systems1,3

• Differences in humidity, ozone levels, and potential vorticity

• +PV anomaly changes vertical distribution of potential temperature & vorticity

• Promotes rapid cyclogenesis

Himawari-8 Airmass RGB • Each color band represents a wavelength (difference) • Different wavelengths capture different layers of

atmosphere

Cour

tesy

of N

OAA

/NCE

P/O

PC

DATA & METHODS

Total Column Ozone & Ozone Anomaly • Used to help quantify

Airmass RGB • Examples of instruments:

Courtesy of Emily Berndt

Himawari-8 Water Vapor

Cooler “high moisture”

Warmer “low moisture”

Upper-layer • 6.2 µm channel • Peak response at ~350 mb

Middle-layer • 6.9 µm channel • Peak response at ~450 mb

Lower-layer • 7.3 µm channel • Peak response at ~650 mb

Scatterometer & Microwave Radiometer • Used to verify hurricane-force 1. Aqua’s Atmospheric

Infrared Sounder (AIRS) 2. S-NPP's Cross-track

Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS)

3. Metop-B’s Infrared Atmospheric Sounding Interferometer (IASI)

Scatterometer • Measures backscatter of radar

signal for wind speed & direction

e.g. Advanced SCATterometer (A/B) Microwave Radiometer

• Measures microwave signal response for only wind speed

e.g. Advanced Microwave Scanning Radiometer (AMSR-2)

Gale-force Storm-force Hurricane-force

Name Date Range

Reasons for Interest

Bering Sea Bomb

December 10-13, 2015

• One of the strongest (924 mb center) non-tropical storms on record

• Large impacts Spring Transition

April 5-9, 2016

• Late season cyclone • Atypical development

TC Songda Transition

October 12-15, 2016

• Lost most of its tropical features

• Atypical extratropical transition & development

1. Early features • PV streamer • Baroclinic leaf

supplying latent heat

• Piece of vorticity absorbed by streamer

2. Rapid Development • Small comma cloud that gets brighter • Clear dry belt using RGB Airmass red colors • Vortex lobe north of system that threatens, eventually

intersecting with original streamer • Anomalous ozone becoming more condensed • AIRS suggesting 150%+ climatology

3. Peak Intensity • Shapiro-Keyser cyclone model features

• Can spot the dry belt, cold front, occlusion using RGB Airmass • Possible warm seclusion in low pressure center • AMSR-2 picks up hurricane-force winds right outside occlusion

Summary • Stratospheric air intrusions +PV Explosive

cyclogenesis Hurricane-force winds • Single Water Vapor channels supply forecasters with

information about jet stream interactions and tropopause folds

• Potential in Airmass RGB + ozone products to identify stratospheric air intrusions

• Can only look at single layer of atmosphere at a time • Doesn’t give info about if air is from stratosphere

• Demonstrated in case studies • Experimental for real-time use

Future Work • Finishing case studies

• Build instructional toolkit for OPC and Alaskan Weather Forecast Offices

• Similar satellite imagery • MERRA-2 global reanalysis model visualization

• More real-time use • Training for RGB Airmass and ozone products

as supplementary information about stratospheric air intrusions

• Apply to GOES-16

Cross-section (170⁰E, 30 ⁰ to 60⁰N) of intrusion for 17 January 2230 UTC with PV anomaly with respect to 2 PVU as dynamical tropopause; (left) overlaid with potential temperature and (right) overlaid with zonal wind

1. Browning, K.A. 1997. The dry intrusion perspective of extra-tropical cyclone development. Meteorol. Appl., 4(4): pp. 317–324. 2. Berndt, E.B., B. T. Zavodsky and M. J. Folmer. 2016. Development and Application of Atmospheric Infrared Sounder Ozone Retrieval Products for Operational Meteorology. IEEE T. Geosci. Remote, 54(2), pp. 958-967. doi: 10.1109/TGRS.2015.2471259. 3. Kew, S.F., M. Sprenger, and H.C. Davies. 2010. Potential Vorticity Anomalies of the Lowermost Stratosphere: A 10-Yr Winter Climatology. Mon. Wea. Rev., 138, 1234–1249, doi: 10.1175/2009MWR3193.1. 4. NOAA & NASA. 2016. GOES-R. Retrieved from www.goes-r.gov. 5. Zavodsky, B.T., A.L. Molthan, and M.J. Folmer. 2013. Multispectral Imagery for Detecting Stratospheric Air Intrusions Associated with Mid-Latitude Cyclones. J. of Oper. Meteor., 1(7): 71-83.

17 Jan 00Z

18 Jan 10Z

19 Jan 18Z

AIRS 19 Jan 00Z

ATMS/CrIS 19 Jan 00Z

18 Jan 20Z

19 Jan 23Z

Red 6.2 μm minus 7.3 μm, representing moisture between 300-700 mb

Green 9.6 μm minus 10.3 μm, representing thermal response & tropopause height

Blue 6.2 μm inverted, representing moisture between 200-400 mb

DRY MOIST

Case: January 17-19, 2016

Developed rapidly despite small size Hard to distinguish its early features

MERRA-2 Global Reanalysis Model Visualization • Intrusion develops January 17 seen by dip of anomalous PV • Stable air associated with stratosphere and less-stable air in troposphere • Counterclockwise rotation around intrusion and max winds at PV gradient

• Before peak intensity, cloud head becomes more zonally oriented

• Vortex shedding